The authors test the effects of common food industry preservatives on the heart rate of the freshwater crustacean Daphnia magna.
Read More...The effect of common food preservatives on the heart rate of Daphnia magna
The authors test the effects of common food industry preservatives on the heart rate of the freshwater crustacean Daphnia magna.
Read More...The impact of Red 40 artificial food dye on the heart rate of Daphnia magna
In this study, potential physiological effects of Red 40 food dye, found in many different food products, are tested using Daphnia magna, a small freshwater crustacean.
Read More...Developing “Off the Shelf” Pancreases for Diabetic Patients Using Bacterial and Kombucha Tea Waste
In this study, the authors investigate the suitability of using bacterial cellulose as a scaffold for cell transplants. Interestingly, this cellulose is a can be found in the discard from a symbiotic culture of bacteria and yeast (SCOBY) used to make kombucha.
Read More...Spelling Bee: A Study on the Motivation and Learning Strategies Among Elementary and Junior-High Student Competitors
This article investigates the study methodologies, learning strategies, and motives of spelling bee participants. The authors identify several important educational implications of this work.
Read More...Does technology help or hurt learning? Evidence from middle school and high school students
Here, recognizing the vastly different opinion held regarding device usage, the authors considered the effects of technology use on middle and high school students' learning effectiveness. Using an anonymous online survey they found partial support that device use at school increases learning effectiveness, but found strong support for a negative effect of technology use at home on learning effectiveness. Based on their findings they suggest that the efficacy of technology depends on environmental context along with other important factors that need consideration.
Read More...Identifying factors, such as low sleep quality, that predict suicidal thoughts using machine learning
Sadly, around 800,000 people die by suicide worldwide each year. Dong and Pearce analyze health survey data to identify associations between suicidal ideation and relevant variables, such as sleep quality, hopelessness, and anxious behavior.
Read More...The effects of food type on mediator-less microbial fuel cell electricity output
The authors look at how different food types impact the ability of bacteria to produce electricity.
Read More...Glyphosate Levels in American Food Products Meet Government Safety Levels Yet Exceed Concentrations Associated with Negative Effects
Glyphosate is the active ingredient in the herbicide Roundup, frequently used in the agricultural industry worldwide. Current literature reveals contradictory findings regarding the effects of glyphosate on vertebrates, leading to concerns about human consumption and differing views on safety levels. Here, authors sought to measure glyphosate levels in common commercially available food products. While some product levels exceed the thresholds at which negative effects have been observed, none exceed government limits.
Read More...Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset
Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.
Read More...Modeling and optimization of epidemiological control policies through reinforcement learning
Pandemics involve the high transmission of a disease that impacts global and local health and economic patterns. Epidemiological models help propose pandemic control strategies based on non-pharmaceutical interventions such as social distancing, curfews, and lockdowns, reducing the economic impact of these restrictions. In this research, we utilized an epidemiological Susceptible, Exposed, Infected, Recovered, Deceased (SEIRD) model – a compartmental model for virtually simulating a pandemic day by day.
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